Neural Machine Translation

Machine Translation Weekly 73: Non-autoregressive MT with Latent Codes

Today, I will comment on a paper on non-autoregressive machine translation that shows a neat trick for increasing output fluency. The title of the paper is Non-Autoregressive Translation by Learning Target Categorical Codes, has authors from several Chinese private and public institutions and will appear at this year’s NAACL Conference. Unlike standard, so-called autoregressive encoder-decoder architectures that decode output sequentially (and in theory in linear time), non-autoregressive models generate all outputs in parallel (and in theory in constant time, regardless […]

Machine Translation Weekly 72: Self-Training for Zero-Shot MT

This week, I will have a look at a pre-print that describes an unconventional setup for zero-shot machine translation. The title of the pre-print is Self-Learning for Zero-Shot Neural Machine Translation and was written by authors from the University of Trento. First of all, I have some doubt about this being really an instance of zero-shot learning (but it is just nitpicking, the paper is interesting regardless of the terminology). In machine learning, zero-shot learning means that a model trained […]

March 15, 2021 Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 71: Explaining Random Feature Attention

Transformers are the neural architecture that underlies most of the current state-of-the-art machine translation and natural language processing in general. One of its major drawbacks is the quadratic complexity of the underlying self-attention mechanism, which in practice limits the sequence length that could be processed by Transformers. There already exist some tricks to deal with that. One of them is local sensitive hashing that was used in the Reformer architecture (see MT Weekly 27). The main idea was computing the […]

March 7, 2021 Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 70: Loss Masking instead of Data Filtering

This week, I will have a closer look at a recent pre-print introducing an alternative for parallel data filtering for machine translation training. The title of the pre-print is Gradient-guided Loss Masking for Neural Machine Translation and comes from CMU and Google. Training data cleanness is a surprisingly important factor for machine translation quality. A large part of the data that we use for training comes from crawling the Internet, so there is no quality guarantee. On the other hand, […]

February 28, 2021 machine translation, Neural MT, NMT

Facilitating Terminology Translation with Target Lemma Annotations

Most of the recent work on terminology integration in machine translation has assumed that terminology translations are given already inflected in forms that are suitable for the target language sentence. In day-to-day work of professional translators, however, it is seldom the case as translators work with bilingual glossaries where terms are given in their dictionary forms; finding the right target language form is part of the translation process… We argue that the requirement for apriori specified target language forms is […]

February 28, 2021 machine translation, Neural MT, NMT

Gamified Crowdsourcing for Idiom Corpora Construction

Learning idiomatic expressions is seen as one of the most challenging stages in second language learning because of their unpredictable meaning. A similar situation holds for their identification within natural language processing applications such as machine translation and parsing… The lack of high-quality usage samples exacerbates this challenge not only for humans but also for artificial intelligence systems. This article introduces a gamified crowdsourcing approach for collecting language learning materials for idiomatic expressions; a messaging bot is designed as an […]

February 28, 2021 machine translation, Neural MT, NMT

Two Demonstrations of the Machine Translation Applications to Historical Documents

We present our demonstration of two machine translation applications to historical documents. The first task consists in generating a new version of a historical document, written in the modern version of its original language… The second application is limited to a document’s orthography. It adapts the document’s spelling to modern standards in order to achieve an orthography consistency and accounting for the lack of spelling conventions. We followed an interactive, adaptive framework that allows the user to introduce corrections to […]

February 28, 2021 machine translation, Neural MT, NMT

Learning Skill Equivalencies Across Platform Taxonomies

Assessment and reporting of skills is a central feature of many digital learning platforms. With students often using multiple platforms, cross-platform assessment has emerged as a new challenge… While technologies such as Learning Tools Interoperability (LTI) have enabled communication between platforms, reconciling the different skill taxonomies they employ has not been solved at scale. In this paper, we introduce and evaluate a methodology for finding and linking equivalent skills between platforms by utilizing problem content as well as the platform’s […]

February 28, 2021 machine translation, Neural MT, NMT

On Automatic Parsing of Log Records

Software log analysis helps to maintain the health of software solutions and ensure compliance and security. Existing software systems consist of heterogeneous components emitting logs in various formats… A typical solution is to unify the logs using manually built parsers, which is laborious. Instead, we explore the possibility of automating the parsing task by employing machine translation (MT). We create a tool that generates synthetic Apache log records which we used to train recurrent-neural-network-based MT models. Models’ evaluation on real-world […]

February 28, 2021 machine translation, Neural MT, NMT

The first large scale collection of diverse Hausa language datasets

Hausa language belongs to the Afroasiatic phylum, and with more first-language speakers than any other sub-Saharan African language. With a majority of its speakers residing in the Northern and Southern areas of Nigeria and the Republic of Niger, respectively, it is estimated that over 100 million people speak the language… Hence, making it one of the most spoken Chadic language. While Hausa is considered well-studied and documented language among the sub-Saharan African languages, it is viewed as a low resource […]

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